Abstract
The world economy depends on information systems. Business value resides in the data stored on Information Technology (IT) systems and on the processes run with those data. Malicious actors target these IT systems to extract value out of them using different cyberattacks. Denial of Service (DoS) attacks are a common and harmful method to render IT systems connected to the Internet and, consequently, business processes running on top of them, unavailable. Cybersecurity researchers in the industry and academia are in search of early warning and detection systems to detect and mitigate these DoS attacks. This article proposes a novel early detection strategy for DoS attacks based on the information provided by Horizontal Visibility Graphs (HVG) and Natural Visibility Graphs (VG) obtained out of the network flows monitored at the receiving end of the attack. From the primary results obtained, this strategy can detect a DoS attack under 70ms and 30 packets. These results point out that the application HVGs and VGs is a relevant and promising research direction to prevent or mitigate the impact of a DoS attack.

Abstract
Nowadays ransomware attacks have become one of the main problems organizations face. The threat of ransomware attacks, with their capacity to paralyze entire organizations, creates the need to develop a ransomware recovery utility function to help further prepare for the impact of such attacks and enhance the organization's knowledge and perception of risk. This work proposes a ransomware recovery utility function that aims to estimate the impact of a ransomware attack measured in manpower hours till recovery and taking into account different devices and different scenarios.

Abstract
Multi-Access Edge Computing (MEC) represents the central concept that enables the creation of new applications and services that bring the benefits of edge computing to networks and users. By implementing applications and services at the edge, close to users and their devices, it becomes possible to take advantage of extremely low latency, substantial bandwidth, and optimized resource usage. However, enabling this approach requires careful integration between the MEC framework and the open 5G core. This work is dedicated to designing a new service that extends the functionality of the Multi-Access Traffic Steering (MTS) API, acting as a strategic bridge between the realms of MEC and the 5G core. To accomplish this objective, we utilize free5GC (open-source project for 5G core) as our 5G core, deployed on the Kubernetes cluster. The proposed service is validated using this framework, involving scenarios of high user density. To conclude whether the discussed solution is valid, KPIs of 5G MEC applications described in the scientific community were sought to use as a comparison parameter. The results indicate that the service effectively addresses the described issues while demonstrating its feasibility in various use cases such as e-Health, Paramedic Support, Smart Home, and Smart Farms.

Abstract
Simple Summary Due to limited proteomic data for rabbit spermatozoa and less comprehensive databases compared to humans, we conducted a combined bioinformatic analysis of the proteome of rabbit X (RX) and human X and Y (HX and HY) chromosomes to identify membrane-associated proteins, particularly those accessible from the cell surface, for potential applications in sperm sexing techniques. Our analysis found 100 (RX), 211 (HX), and 3 (HY) plasma membrane or cell surface-associated proteins, of which 61, 132, and 3 are potentially accessible from the cell surface. Notably, among the HX targets, 60 could serve as additional RX targets not previously identified, bringing the total to 121 RX targets. Furthermore, at least 53 out of the 114 potential common HX and RX targets chromosomes have been previously identified in human spermatozoa, emphasizing their potential as targets of X-chromosome-bearing spermatozoa. The utility of these proteins as targets of rabbit X-chromosome-bearing spermatozoa warrants further exploration.Abstract Studying proteins associated with sex chromosomes can provide insights into sex-specific proteins. Membrane proteins accessible through the cell surface may serve as excellent targets for diagnostic, therapeutic, or even technological purposes, such as sperm sexing technologies. In this context, proteins encoded by sex chromosomes have the potential to become targets for X- or Y-chromosome-bearing spermatozoa. Due to the limited availability of proteomic studies on rabbit spermatozoa and poorly annotated databases for rabbits compared to humans, a bioinformatic analysis of the available rabbit X chromosome proteome (RX), as well as the human X (HX) and Y (HY) chromosomes proteome, was conducted to identify potential targets that could be accessible from the cell surface and predict which of the potential targets identified in humans might also exist in rabbits. We identified 100, 211, and 3 proteins associated with the plasma membrane or cell surface for RX, HX, and HY, respectively, of which 61, 132, and 3 proteins exhibit potential as targets as they were predicted to be accessible from the cell surface. Cross-referencing the potential HX targets with the rabbit proteome revealed an additional 60 proteins with the potential to be RX targets, resulting in a total of 121 potential RX targets. In addition, at least 53 possible common HX and RX targets have been previously identified in human spermatozoa, emphasizing their potential as targets of X-chromosome-bearing spermatozoa. Further proteomic studies on rabbit sperm will be essential to identify and validate the usefulness of these proteins for application in rabbit sperm sorting techniques as targets of X-chromosome-bearing spermatozoa.

Abstract
With the massive data collection from different devices, spanning from mobile devices to all sorts of IoT devices, protecting the privacy of users is a fundamental concern. In order to prevent unwanted disclosures, several Privacy-Preserving Mechanisms (PPMs) have been proposed. Nevertheless, due to the lack of a standardized and universal privacy definition, configuring and evaluating PPMs is quite challenging, requiring knowledge that the average user does not have. In this paper, we propose a privacy toolkit - Privkit - to systematize this process and facilitate automated configuration of PPMs. Privkit enables the assessment of privacy-preserving mechanisms with different configurations, while allowing the quantification of the achieved privacy and utility level of various types of data. Privkit is open source and can be extended with new data types, corresponding PPMs, as well as privacy and utility assessment metrics and privacy attacks over such data. This toolkit is available through a Python Package with several state-of-the-art PPMs already implemented, and also accessible through a Web application. Privkit constitutes a unified toolkit that makes the dissemination of new privacy-preserving methods easier and also facilitates reproducibility of research results, through a repository of Jupyter Notebooks that enable reproduction of research results.

Abstract
In this letter, we introduce the computation-limited (comp-limited) signals, a communication capacity regime where the computational complexity of signal processing is the primary constraint for communication performance, overriding factors such as power or bandwidth. We present the Spectro-Computational (SC) analysis, a novel mathematical framework designed to enhance classic concepts of information theory -such as data rate, spectral efficiency, and capacity - to accommodate the computational complexity overhead of signal processing. We explore a specific Shannon regime where capacity is expected to increase indefinitely with channel resources. However, we identify conditions under which the time complexity overhead can cause capacity to decrease rather than increase, leading to the definition of the comp-limited signal regime. Furthermore, we provide examples of SC analysis and demonstrate that the Orthogonal Frequency Division Multiplexing (OFDM) waveform falls under the comp-limited regime unless the lower-bound computational complexity of the N-point Discrete Fourier Transform (DFT) problem verifies as ohm (N)$ , which remains an open challenge in the theory of computation.